Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot

Azhar Aulia Saputra; Noel Nuo Wi Tay; Yuichiro Toda; János Botzheim; Naoyuki Kubota

doi:10.1109/IROS.2016.7759654

Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot

Azhar Aulia Saputra, Noel Nuo Wi Tay, Yuichiro Toda, János Botzheim, Naoyuki Kubota

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

18 Scopus citations

Abstract

This paper presents Bezier curve based passive neural control applied in bio-inspired locomotion in order to decrease the computational cost implemented for 4 legged animal robot which has 3 joints in each leg. Neural oscillator model is applied for generating the walking pattern in bioinspired locomotion. Bezier curve based optimization represents passive neural control supported by evolutionary algorithm tor representing the relationship equation between neuron signal and reference joint signal. Passive neural control is implemented in order to reduce the neuron complexity in neuro-based locomotion by controlling 3 joints with one signal without decreasing the performance both in walking pattern and in its stability level, whereas one leg is represented by one motor neuron. Therefore, the 4 legged robot is controlled by 4 motor neurons which have feedback connection with ground and inertial sensor. In order to prove the effectiveness, we implemented the model in computer simulation and in a small 4 legged robot. This model can decrease the computational cost so it is possible to apply the model in either animal or humanoid robot with low frequency processor.

Original language	English
Title of host publication	IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4443-4448
Number of pages	6
ISBN (Electronic)	9781509037629
DOIs	https://doi.org/10.1109/IROS.2016.7759654
State	Published - 28 Nov 2016
Externally published	Yes
Event	2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 - Daejeon, Korea, Republic of Duration: 9 Oct 2016 → 14 Oct 2016

Publication series

Name	IEEE International Conference on Intelligent Robots and Systems
Volume	2016-November
ISSN (Print)	2153-0858
ISSN (Electronic)	2153-0866

Conference

Conference	2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016
Country/Territory	Korea, Republic of
City	Daejeon
Period	9/10/16 → 14/10/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

Bezier based optimization
Bio-inspired locomotion
Passive neural control

ASJC Scopus subject areas

Control and Systems Engineering
Software
Computer Vision and Pattern Recognition
Computer Science Applications

Access to Document

10.1109/IROS.2016.7759654

Cite this

Saputra, A. A., Tay, N. N. W., Toda, Y., Botzheim, J., & Kubota, N. (2016). Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot. In IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 4443-4448). Article 7759654 (IEEE International Conference on Intelligent Robots and Systems; Vol. 2016-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IROS.2016.7759654

Saputra, Azhar Aulia ; Tay, Noel Nuo Wi ; Toda, Yuichiro et al. / Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot. IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 4443-4448 (IEEE International Conference on Intelligent Robots and Systems).

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title = "Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot",

abstract = "This paper presents Bezier curve based passive neural control applied in bio-inspired locomotion in order to decrease the computational cost implemented for 4 legged animal robot which has 3 joints in each leg. Neural oscillator model is applied for generating the walking pattern in bioinspired locomotion. Bezier curve based optimization represents passive neural control supported by evolutionary algorithm tor representing the relationship equation between neuron signal and reference joint signal. Passive neural control is implemented in order to reduce the neuron complexity in neuro-based locomotion by controlling 3 joints with one signal without decreasing the performance both in walking pattern and in its stability level, whereas one leg is represented by one motor neuron. Therefore, the 4 legged robot is controlled by 4 motor neurons which have feedback connection with ground and inertial sensor. In order to prove the effectiveness, we implemented the model in computer simulation and in a small 4 legged robot. This model can decrease the computational cost so it is possible to apply the model in either animal or humanoid robot with low frequency processor.",

keywords = "Bezier based optimization, Bio-inspired locomotion, Passive neural control",

author = "Saputra, \{Azhar Aulia\} and Tay, \{Noel Nuo Wi\} and Yuichiro Toda and J{\'a}nos Botzheim and Naoyuki Kubota",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016 ; Conference date: 09-10-2016 Through 14-10-2016",

year = "2016",

month = nov,

day = "28",

doi = "10.1109/IROS.2016.7759654",

language = "English",

series = "IEEE International Conference on Intelligent Robots and Systems",

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Saputra, AA, Tay, NNW, Toda, Y, Botzheim, J & Kubota, N 2016, Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot. in IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems., 7759654, IEEE International Conference on Intelligent Robots and Systems, vol. 2016-November, Institute of Electrical and Electronics Engineers Inc., pp. 4443-4448, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016, Daejeon, Korea, Republic of, 9/10/16. https://doi.org/10.1109/IROS.2016.7759654

Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot. / Saputra, Azhar Aulia; Tay, Noel Nuo Wi; Toda, Yuichiro et al.
IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems. Institute of Electrical and Electronics Engineers Inc., 2016. p. 4443-4448 7759654 (IEEE International Conference on Intelligent Robots and Systems; Vol. 2016-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Saputra, Azhar Aulia

AU - Tay, Noel Nuo Wi

AU - Toda, Yuichiro

AU - Botzheim, János

AU - Kubota, Naoyuki

PY - 2016/11/28

Y1 - 2016/11/28

N2 - This paper presents Bezier curve based passive neural control applied in bio-inspired locomotion in order to decrease the computational cost implemented for 4 legged animal robot which has 3 joints in each leg. Neural oscillator model is applied for generating the walking pattern in bioinspired locomotion. Bezier curve based optimization represents passive neural control supported by evolutionary algorithm tor representing the relationship equation between neuron signal and reference joint signal. Passive neural control is implemented in order to reduce the neuron complexity in neuro-based locomotion by controlling 3 joints with one signal without decreasing the performance both in walking pattern and in its stability level, whereas one leg is represented by one motor neuron. Therefore, the 4 legged robot is controlled by 4 motor neurons which have feedback connection with ground and inertial sensor. In order to prove the effectiveness, we implemented the model in computer simulation and in a small 4 legged robot. This model can decrease the computational cost so it is possible to apply the model in either animal or humanoid robot with low frequency processor.

AB - This paper presents Bezier curve based passive neural control applied in bio-inspired locomotion in order to decrease the computational cost implemented for 4 legged animal robot which has 3 joints in each leg. Neural oscillator model is applied for generating the walking pattern in bioinspired locomotion. Bezier curve based optimization represents passive neural control supported by evolutionary algorithm tor representing the relationship equation between neuron signal and reference joint signal. Passive neural control is implemented in order to reduce the neuron complexity in neuro-based locomotion by controlling 3 joints with one signal without decreasing the performance both in walking pattern and in its stability level, whereas one leg is represented by one motor neuron. Therefore, the 4 legged robot is controlled by 4 motor neurons which have feedback connection with ground and inertial sensor. In order to prove the effectiveness, we implemented the model in computer simulation and in a small 4 legged robot. This model can decrease the computational cost so it is possible to apply the model in either animal or humanoid robot with low frequency processor.

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ER -

Saputra AA, Tay NNW, Toda Y, Botzheim J, Kubota N. Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot. In IROS 2016 - 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems. Institute of Electrical and Electronics Engineers Inc. 2016. p. 4443-4448. 7759654. (IEEE International Conference on Intelligent Robots and Systems). doi: 10.1109/IROS.2016.7759654

Bezier curve model for efficient bio-inspired locomotion of low cost four legged robot

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this